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Business Cycle Asymmetries: Characterisation and Testing based on Markov-Switching Autoregressions

  • Hans-Martin Krolzig
  • Michael Clements

We propose testing for business cycle first-moment asymmetries in Markov-switching autoregressive (MS-AR) models. We derive the parametric restrictions on MS-AR models that rule out types of asymmetries such as deepness, steepness, and sharpness, and set out a testing procedure based on Wald statistics which have standard asymptotics. For a two-regime model, such as that popularised by Hamilton (1989), we show that deepness implies sharpness (and vice versa) while the process is always non-step. We illustrated with two and three-state MS-AR models of US GNP growth, and models of US investment and consumption growth. Our findings are compared with those obtained from standard non-parametric tests, which are unable to distinguish between first-moment asymmetries and heteroscedasticity.

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Paper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 2000-W32.

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Date of creation: 01 Oct 2000
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Handle: RePEc:oxf:wpaper:2000-w32
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  12. GORDON, Stephen, 1995. "Stochastic Trends, Deterministic Trends and Business Cycle Turning Points," Cahiers de recherche 9503, Université Laval - Département d'économique.
  13. Krolzig, Hans-Martin & Sensier, Marianne, 2000. "A Disaggregated Markov-Switching Model of the Business Cycle in UK Manufacturing," Manchester School, University of Manchester, vol. 68(4), pages 442-60, Special I.
  14. Hamilton, James D & Gang, Lin, 1996. "Stock Market Volatility and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 573-93, Sept.-Oct.
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  24. Michael P. Clements & Hans-Martin Krolzig, 1998. "A comparison of the forecast performance of Markov-switching and threshold autoregressive models of US GNP," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages C47-C75.
  25. Filardo, Andrew J, 1994. "Business-Cycle Phases and Their Transitional Dynamics," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 299-308, July.
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